AIMC Topic: Deep Learning

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Deep learning enabled liquid-based cytology model for cervical precancer and cancer detection.

Nature communications
Deep learning (DL) enabled liquid-based cytology has potential for cervical cancer screening or triage. Here, we develop a DL model using whole cytology slides from 17,397 women and test it on 10,826 additional cases through a three-stage process. Th...

Hybrid of DSR-GAN and CNN for Alzheimer disease detection based on MRI images.

Scientific reports
In this paper, we propose a deep super-resolution generative adversarial network (DSR-GAN) combined with a convolutional neural network (CNN) model designed to classify four stages of Alzheimer's disease (AD): Mild Dementia (MD), Moderate Dementia (M...

im7G-DCT: A two-branch strategy model based on improved DenseNet and transformer for m7G site prediction.

Computational biology and chemistry
N-7 methylguanosine (m7G) is an important RNA modification that plays a key role in regulating gene expression and cellular physiological functions. Medical research has shown that m7G is closely associated with the development of a variety of diseas...

Collaborative twin actors framework using deep deterministic policy gradient for flexible batch processes.

Neural networks : the official journal of the International Neural Network Society
Due to its inherent efficiency in the process industry for achieving desired products, batch processing is widely acknowledged for its repetitive nature. Batch-to-batch learning control has traditionally been esteemed as a robust strategy for batch p...

Broad learning system based on fractional order optimization.

Neural networks : the official journal of the International Neural Network Society
Due to its efficient incremental learning performance, the broad learning system (BLS) has received widespread attention in the field of machine learning. Scholars have found in algorithm research that using the maximum correntropy criterion (MCC) ca...

Adaptive estimation of instance-dependent noise transition matrix for learning with instance-dependent label noise.

Neural networks : the official journal of the International Neural Network Society
Instance-dependent noise (IDN) widely exists in real-world datasets, seriously hindering the effective application of deep neural networks. In contrast to class-dependent noise, IDN is influenced not solely by the class but also by the intrinsic feat...

YOLOv8-G2F: A portable gesture recognition optimization algorithm.

Neural networks : the official journal of the International Neural Network Society
Hand gesture recognition (HGR) is a significant research area with applications in human-computer interaction, artificial intelligence, and more. In the early stage of development of HGR, there are high hardware costs and large usage requirements. To...

Recent Advances in Artificial Intelligence for Precision Diagnosis and Treatment of Bladder Cancer: A Review.

Annals of surgical oncology
BACKGROUND: Bladder cancer is one of the top ten cancers globally, with its incidence steadily rising in China. Early detection and prognosis risk assessment play a crucial role in guiding subsequent treatment decisions for bladder cancer. However, t...

Joint semi-supervised and contrastive learning enables domain generalization and multi-domain segmentation.

Medical image analysis
Despite their effectiveness, current deep learning models face challenges with images coming from different domains with varying appearance and content. We introduce SegCLR, a versatile framework designed to segment images across different domains, e...

Video-based multi-target multi-camera tracking for postoperative phase recognition.

International journal of computer assisted radiology and surgery
PURPOSE: Deep learning methods are commonly used to generate context understanding to support surgeons and medical professionals. By expanding the current focus beyond the operating room (OR) to postoperative workflows, new forms of assistance are po...